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概要と使いどころ
Design, implement, and evaluate risk-based software tests across unit, integration, contract, end-to-end, and regression layers. Use when adding tests, reproducing bugs, improving coverage, diagnosing flaky tests, or defining a test strategy; do not use to change production behavior unless the user also requests implementation.
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Analyze NFT projects for investment decisions — evaluate fundamentals, identify red flags, assess risk, and provide buy/hold/avoid recommendations
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Discover and analyze trending GitHub repositories from TrendShift and other sources — evaluate usefulness, extract learnings, and identify valuable skills/tools
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Evaluate and install ecosystem tools (Hermes plugins, skills, integrations) — assess complexity vs. benefit before installation, show examples for visual tools, and avoid "cloned but not configured" states.
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Evaluate and maximize GitHub repo quality from 7/10 to 10/10 perfect
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Evaluate any address for home buyers and renters.
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Address GitHub PR review feedback at line, file, and PR level — fetch, evaluate, fix, commit, and resolve. Use when given a PR URL, a review-comment URL, or a PR-level comment URL. Triggers: GitHub discussion URLs, "fix this review comment", "address PR feedback", "resolve PR comments", PR URLs with #discussion_, #issuecomment-, or #pullrequestreview- fragments.
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Generate architecture and design documents for implemented code changes with risk-based depth selection. Automatically evaluates risk signals, layer spread, and change magnitude to choose documentation level (A/B/C). Use after completing a feature, before merging a PR that touches multiple layers or sensitive areas (auth, infra, migrations, payments), or when an implemented change needs a design record or ADR.
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Black-box evaluation of a shipped LLM feature — adversarial probes for hallucination, prompt-injection, and cost-runaway vs stated expectations. Not RAG/embedding. Triggers 'review my chatbot'.
日本語の概要は準備中です。原文の説明を表示しています。
Agents work in parallel on the same task; judges evaluate and select the winner.
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Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy. Triggers: create a skill, new skill, build a skill, skill creation, write a SKILL.md, evaluate skill, test skill, skill eval, benchmark skill, optimize skill description.
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[Content] Use when you need to evaluate business idea viability: Business Model Canvas, financial projections, risk matrix, go-to-market, execution plan.
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Evaluates candidate profiles against a job description and hiring criteria. Use when the user provides candidate profiles plus a role definition and wants consistent screening, matched requirements, and an interview recommendation.
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Evaluates potential channel, integration, affiliate, or strategic partners. Use when the user provides partner profiles plus partnership goals and wants fit scoring, partnership type, and outreach priority.
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Evaluate UI/flows from cognitive load, error prevention, and accessibility perspectives. Apply when reviewing UX, discussing user confusion, high drop-off, or form usability issues.
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Triage a single GitHub PR by PR number. Check out the PR's branch, detect conflicts with the target branch via `gh pr status` (and label the PR with `cc-resolve-conflict` if any are found), generate and evaluate a fix plan via create-review-fix-plan, then take action (add cc-fix-onetime label if fixes are needed, or merge the PR if it's ready).
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Evaluate, rewrite, and select WeChat Official Account article titles for open rate, depth, reader promise, and account tone. Use when drafting, reviewing, publishing, or revising公众号文章标题, especially when titles may be generic, stale, clickbait, AI-flavored, or misaligned with the article's commercial/editorial intent.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluate authorized wireless networks for handshake, PMKID, rogue AP, and enterprise auth weaknesses.
日本語の概要は準備中です。原文の説明を表示しています。
Find, build, evaluate, and improve systems using decision models. Use for bounded classification, routing, ranking, Choice/Score/Noul, decision-model composition, evaluation harnesses, prompt/program hill climbing, and Software 3.0 workflows across software, business, organizations, and life. Separate models, code, and human judgment. TypeSafe Jev is the default hosted exemplar. Not for straightforward arithmetic, prose rewriting, or provider setup alone.
日本語の概要は準備中です。原文の説明を表示しています。
Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure
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AI-powered design review for Figma components with weighted dual-scoring system. Evaluates Style Guide Implementation (70%) and LLM Metadata Accessibility (30%). For export, hands off to atomic-design skill.
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Solves complex, open-ended problems using an evolutionary search mechanism inspired by genetic algorithms. Generates a diverse population of candidate answers, scores them against a rubric, then iteratively applies selection, crossover, and mutation to breed progressively better solutions. Use this skill whenever the user wants to explore a solution space deeply, asks for the "best" answer to a subjective or multi-dimensional problem, wants to evaluate competing approaches and distill the strongest, or uses any of these triggers: "evolutionary search", "genetic algorithm", "evolve an answer", "breed solutions", "population-based search", or phrases like "give me multiple approaches and refine the best one". Also trigger when the problem is complex, open-ended, or has no obvious single correct answer and the user wants a high-quality, well-explored result, not just a quick response.
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Assess whether source code is ready to deploy to Azure — the check BEFORE infrastructure work. Evaluates build health, app completeness, dependencies and local services, stack compatibility, and deployment feasibility.
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Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.
日本語の概要は準備中です。原文の説明を表示しています。